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Record W2314168233 · doi:10.1093/ijrl/eev017

Saeteomin Asylum Seekers: The Law and Policy Response

2015· article· en· W2314168233 on OpenAlexaboutno aff
Andrew Wolman, Guanghe Li

Bibliographic record

VenueInternational Journal of Refugee Law · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicKorean Peninsula Historical and Political Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeePolitical sciencePrincipal (computer security)Asylum seekerJurisprudenceLawSeekersComputer security

Abstract

fetched live from OpenAlex

Over the past decade, developed countries have received significant numbers of North Korean asylum seekers. Some of these asylum seekers have managed to travel to developed countries without first travelling to South Korea. It has gradually become clear that many others are so-called ‘Saeteomin’ or ‘new settlers’, meaning North Koreans who have first settled in South Korea. This article will examine the law and policy response of destination countries to the influx of Saeteomin, especially focusing on the United States, the United Kingdom, and Canada. It will demonstrate that destination countries have reacted in three principal ways to the Saeteomin asylum seekers. First, they have evolved a more restrictive refugee jurisprudence in key areas affecting Saeteomin. Second, they have shared asylum seeker fingerprints with the South Korean authorities in an effort to help distinguish Saeteomin who deny having settled in South Korea from North Koreans who have not previously settled in South Korea. Third, the UK and Canada have attempted to deter Saeteomin asylum seekers through adding South Korea to safe country lists. This article argues that while these responses may be generally permissible under international law, they result in a number of problematic or potentially negative consequences. It will conclude by suggesting policy measures that South Korea and destination countries can take to better manage the issue of Saeteomin asylum seekers by adequately protecting the privacy of personal data and focusing on reducing the impetus to seek asylum outside South Korea.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.938
Threshold uncertainty score0.442

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.351
Teacher spread0.320 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2015
Admission routes1
Has abstractyes

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